"Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory."
Focusing on the social networks and connections of migrant communities, the dynamics of transnational social practices, and the implications of social capital.
Social network theory: The theoretical foundations of social network analysis, including concepts such as nodes, ties, structural holes, and centrality.
Migration networks: The study of the patterns and dynamics of social networks among migrants, including their formation, evolution, and impact on migration outcomes.
Immigrant communities: The exploration of the social networks that form among immigrants in host societies, including the role of ethnic enclaves and the formation of transnational ties.
Social capital: The examination of the resources that are generated through social networks, including access to information, resources, and social support.
Social inclusion/exclusion: The analysis of how social networks can contribute to the inclusion or exclusion of migrants in host societies, including the role of discrimination and social exclusion.
Transnationalism: The study of the ways in which migrants maintain and develop social networks across national borders, and the impact of these networks on migration outcomes and integration processes.
Network visualization: The use of visualization techniques to represent and analyze social network data, including the use of network diagrams and other graphical representations.
Network analysis software: An introduction to the software tools used for social network analysis, including Gephi, NodeXL, and UCINet.
Qualitative methods: An overview of the qualitative research methods used in social network analysis, including interviews, ethnography, and case studies.
Quantitative methods: An overview of the quantitative research methods used in social network analysis, including statistical analysis, network models, and social network analysis software tools.
Data collection: An introduction to the different methods used to collect social network data, including surveys, name generators, and archival data.
Data analysis: An overview of the different methods used to analyze social network data, including descriptive statistics, centrality measures, and network visualization techniques.
Network formation: An analysis of the factors that influence the formation of social networks, including demographic factors, social structure, and migration policies.
Migration trajectories: An exploration of how social networks influence the trajectories of migrants, including their choice of migration destinations, the length of their stay, and their eventual return migration.
Social network interventions: An examination of the potential for social network interventions to improve the social and economic outcomes of migrants, including the use of social network-based job referral programs and community organizing initiatives.
Egocentric network analysis: This type of analysis focuses on the networks of individual migrants, rather than on the networks between groups of migrants. This involves examining the characteristics of the individual's social network, such as the size, structure, and composition of their network.
Whole network analysis: This type of analysis looks at the relationships between multiple individuals or groups in a network, including the structure and dynamics of the network as a whole.
Dyadic analysis: This type of analysis examines the relationships between two individuals or groups, such as the interactions between migrants and immigration officials.
Multiplex network analysis: This type of analysis involves examining multiple types of relationships between individuals or groups, such as social ties, economic ties, and family ties. This can be helpful in understanding the complex web of relationships that exist within migrant networks.
Longitudinal network analysis: This type of analysis tracks changes in a network over time, such as changes in social ties, migration patterns, and social support systems.
Spatial network analysis: This type of analysis examines the spatial relationships between individuals and groups in a network, such as the patterns of migration and settlement within a community of migrants.
Intersectional network analysis: This type of analysis looks at how different identities intersect within migrant networks, such as the ways in which gender, race, and social class impact social ties and access to resources.
"It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them."
"Examples of social structures commonly visualized through social network analysis include social media networks, meme spread, information circulation, friendship and acquaintance networks, peer learner networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships."
"These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines."
"It has also gained significant popularity in the following - anthropology, biology, demography, communication studies, economics, geography, history, information science, organizational studies, political science, public health, social psychology, development studies, sociolinguistics, and computer science, education and distance education research."
"The advantages of SNA are twofold. Firstly, it can process a large amount of relational data and describe the overall relational network structure."
"System and parameter selection to confirm the influential nodes in the network, such as in-degree and out-degree centrality."
"Through analyzing nodes, clusters, and relations, the communication structure and position of individuals can be clearly described."
"Social network analysis has emerged as a key technique in modern sociology."
"Examples of social structures commonly visualized through social network analysis include... disease transmission."
"These networks are often visualized through sociograms, in which nodes are represented as points and ties are represented as lines, [including] collaboration graphs."
"[SNA] has gained significant popularity in anthropology, biology, demography, communication studies, economics, geography, history, information science, organizational studies, political science, public health, social psychology, development studies, sociolinguistics, computer science, education, and distance education research."
"It has also gained significant popularity in... social psychology."
"SNA context and choose which parameters to define the 'center' according to the characteristics of the network."
"Examples of social structures commonly visualized through social network analysis include... knowledge networks."
"Examples of social structures commonly visualized through social network analysis include... meme spread."
"Examples of social structures commonly visualized through social network analysis include... difficult working relationships."
"It has also gained significant popularity in... political science."
"...is now commonly available as a consumer tool (see the list of SNA software)."
"It has also gained significant popularity in... education and distance education research."